• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.17 no.3
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• pp.139-170
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• 2013

We extend a p-hierarchical decomposition of the second degree finite element space of N$\acute{e}$d$\acute{e}$lec for tetrahedral meshes in three dimensions given in [1] to meshes with hexahedral elements, and derive p-hierarchical decompositions of the second degree finite element space of Raviart-Thomas in two dimensions for triangular and quadrilateral meshes. After having proved stability of these subspace decompositions and requiring certain saturation assumptions to hold, we construct a local a posteriori error estimator for fem and bem coupling of a time-harmonic electromagnetic eddy current problem in $\mathbb{R}^3$. We perform some numerical tests to underline reliability and efficiency of the estimator and test its usefulness in an adaptive refinement scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11C
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• pp.1551-1563
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• 2004

This paper proposes a hierarchical approach to shape model ASM using wavelet transform. Local structure model fitting in the ASM plays an important role in model-based pose and shape analysis. The proposed algorithm can robustly find good solutions in complex images by using wavelet decomposition. we also proposed effective method that estimates and corrects object's movement by using Wavelet transform-based hierarchical motion estimation scheme for ASM-based, real-time video tracking. The proposed algorithm has been tested for various sequences containing human motion to demonstrate the improved performance of the proposed object tracking.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.155-160
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• 2006

This paper presents the hierarchical block matching algorithm using the 4 subbands of the wavelet transformation and the thresholding method. The proposed algorithm improves the PSNR performance of the reconstructed image using the 4 subbands of the wavelet transformation and reduces the computational complexity by thresholding the motion vector. The experimental results of the proposed algorithm for 'Carphone' image and 'Mother and Daughter' image show that if the thresholding value is 0, the computational complexity is increasing up to 16% and the PSNR performance of the reconstructed image improves the 0.16dB in comparison with that of the existing. hierarchical motion estimation algorithm. In addition, as the thresholding value is increasing, the computational complexity reduces up to 8% and the PSNR performance of the reconstructed image is similar.

• ETRI Journal
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• v.42 no.6
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• pp.922-931
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• 2020

A hierarchical iterative algorithm for the canonical polyadic decomposition (CPD) of tensors is proposed by improving the traditional conjugate gradient least squares (CGLS) method. Methods based on algebraic operations are investigated with the objective of estimating the direction of arrival (DoA) and polarization parameters of signals impinging on an array with electromagnetic (EM) vector-sensors. The proposed algorithm adopts a hierarchical iterative strategy, which enables the algorithm to obtain a fast recovery for the highly collinear factor matrix. Moreover, considering the same accuracy threshold, the proposed algorithm can achieve faster convergence compared with the alternating least squares (ALS) algorithm wherein the highly collinear factor matrix is absent. The results reveal that the proposed algorithm can achieve better performance under the condition of fewer snapshots, compared with the ALS-based algorithm and the algorithm based on generalized eigenvalue decomposition (GEVD). Furthermore, with regard to an array with a small number of sensors, the observed advantage in estimating the DoA and polarization parameters of the signal is notable.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.11b
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• pp.21-25
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• 1999

Wavelet transform decomposes a video frame into a set of subframes with different resolutions corresponding to different frequency bands. The block size of highest layer subframe is too small to estimate correct motion. To decrease this aperture problem in the approximation frame, multiresolution motion estimation (MRME) using hierarchical block matching is presented in this paper. In the multiresolution motion estimation approach, motion vectors in the subframes are estimated by the motion vectors in the approximation frame and are refined at each subframe. It reduces computational time in motion estimation. It is shown that our MRME approach has a superior performance than traditional MRME approaches.

• Journal of Broadcast Engineering
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• v.1 no.1
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• pp.7-13
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• 1996

MASF is a kind of temporal filter proposed for noise reduction and temporal band limitation. MASF uses motion vectors to extract temporal information in spatial domain. Therefore, inaccurate motion information causes some distortions in MASF operation. Currently, bilinear interpolation after BMA(Block Matching Algorithm) is used for the motion estimation sheme of MASF. But, this method results in unreliable estimation when the object in image sequence has larger movement than the maximum displacement assumed in BMA or the input images are severely corrupted with noise. In order to i:;olve this problem, we analyse the effect of inaccurate motion on MASF and propose a hierarchical motion estimation algorithm based on the analysis results. Experimental results show that the proposed method produces reliable output under large motion and noisy situations.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.254-261
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• 2007

In this paper, we propose a blind equalization method for advanced terrestrial digital multimedia broadcasting (AT-DMB) systems which use hierarchical modulation. The AT-DMB system adopts hierarchical 16-ary quadrature amplitude modulation (16-QAM) to ensure backward-compatibly with the differential quadrature phase shift keying (DQPSK) signal of the legacy terrestrial digital multimedia broadcasting (T-DMB) systems and to support higher transmission rate. Due to the hierarchical modulation, the conventional T-DMB signal and the additional signal have different error rate at same signal to noise ratio (SNR). By weighting the decided symbols differently according to the reliability of the symbols, i.e., high priority symbol with low error rate and low priority symbol with high error rate, we can improve the channel estimation accuracy. In this paper, we analyze SNR loss by hierarchical modulation and confirm it through simulations. Moreover, through simulations, we verify that the proposed weighting method improve BER compared to the no-weighting method.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.56-59
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• 1997

Vision system is mainly consist of three parts of perception, action. One of these parts, perception system detects visual target in surrounding environment. Block-based motion estimation with compensation is one of the popular approaches without accuracy. The hierarchical method the optical flow with gradient is used to improve optical flow time delay.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.179-192
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• 2001

When a statistical model has a hierarchical structure such as multilayer perceptrons in neural networks or Gaussian mixture density representation, the model includes distribution with unidentifiable parameters when the structure becomes redundant. Since the exact structure is unknown, we need to carry out statistical estimation or learning of parameters in such a model. From the geometrical point of view, distributions specified by unidentifiable parameters become a singular point in the parameter space. The problem has been remarked in many statistical models, and strange behaviors of the likelihood ratio statistics, when the null hypothesis is at a singular point, have been analyzed so far. The present paper studies asymptotic behaviors of the maximum likelihood estimator and the Bayesian predictive estimator, by using a simple cone model, and show that they are completely different from regular statistical models where the Cramer-Rao paradigm holds. At singularities, the Fisher information metric degenerates, implying that the cramer-Rao paradigm does no more hold, and that he classical model selection theory such as AIC and MDL cannot be applied. This paper is a first step to establish a new theory for analyzing the accuracy of estimation or learning at around singularities.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.131-136
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• 1997

We present a method to estimate a dense and sharp depth map using multiple cameras for the application to flexible video production. A key issue for obtaining sharp depth map is how to overcome the harmful influence of occlusion. Thus, we first propose to selectively use the depth information from multiple cameras. With a simple sort and discard technique, we resolve the occlusion problem considerably at a slight sacrifice of noise tolerance. However, boundary overreach of more textured area to less textured area at object boundaries still remains to be solved. We observed that the amount of boundary overreach is less than half the size of the matching window and, unlike usual stereo matching, the boundary overreach with the proposed occlusion-overcoming method shows very abrupt transition. Based on these observations, we propose a hierarchical estimation scheme that attempts to reduce boundary overreach such that edges of the depth map coincide with object boundaries on the one hand, and to reduce noisy estimates due to insufficient size of matching window on the other hand. We show the hierarchical method can produce a sharp depth map for a variety of images.